1. Joint Modeling
1.1 Trace plots for convergence check
The current MCMC setting is:
- 4000000 iteration;
- 3000000 burn-in;
- 1000 thinning.
1.2 Gelman and Rubin’s convergence check
## Potential scale reduction factors:
##
## Point est. Upper C.I.
## HDevsum 1.014 1.07
## LDevsum 0.999 1.00
## dh0 1.046 1.18
## dh1 1.060 1.24
## dh2 1.008 1.04
## dl0 1.003 1.02
## dl1 1.021 1.09
##
## Multivariate psrf
##
## 1.05
1.3 ACF Plots
Here we plotted ACF plots for the following variables:
- Total deviance;
- Variables that didn’t pass the convergence check.
1.4 WAIC results
| LevelH | LevelL | |
|---|---|---|
| DIC | 1212.97410 | 22619.9920 |
| DIC3 | 1153.82042 | 22720.2001 |
| PWAIC | 42.29597 | 259.0566 |
| WAIC | 1180.53524 | 22743.0553 |
2. Separate Modeling of High-Level
2.1 Trace plots for convergence check
The current MCMC setting is:
- 4000000 iteration;
- 3000000 burn-in;
- 1000 thinning.
2.2 Gelman and Rubin’s convergence check
## Potential scale reduction factors:
##
## Point est. Upper C.I.
## HDevsum 1.00 1.01
## dh0 1.05 1.20
## dh1 1.10 1.39
## dh2 1.04 1.18
##
## Multivariate psrf
##
## 1.07
2.3 ACF Plots
Here we plotted ACF plots for the following variables:
- Total deviance;
- Variables that didn’t pass the convergence check.
2.4 WAIC results
| H2 | |
|---|---|
| DIC | 1360.30146 |
| DIC3 | 1237.99281 |
| PWAIC | 87.01432 |
| WAIC | 1304.51018 |
3. Separate Modeling for Low-level
3.1 Trace plots for convergence check
The current MCMC setting is:
- 4000000 iteration;
- 3000000 burn-in;
- 1000 thinning.
3.2 Gelman and Rubin’s convergence check
## Potential scale reduction factors:
##
## Point est. Upper C.I.
## LDevsum 1 1.01
## dl0 1 1.00
## dl1 1 1.00
##
## Multivariate psrf
##
## 1
3.3 ACF Plots
Here we plotted ACF plots for the following variables:
- Total deviance;
- Variables that didn’t pass the convergence check.
3.4 WAIC results
| L1 | |
|---|---|
| DIC | 22752.4415 |
| DIC3 | 22831.9295 |
| PWAIC | 327.7769 |
| WAIC | 22868.2410 |